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Record W3161196879 · doi:10.1080/02703181.2021.1920654

The Importance of Adapting Functional Test Instructions for Older Adults with Neurocognitive Disorders

2021· article· en· W3161196879 on OpenAlexaff
Audrey-Ann Blais, Cynthia Tremblay, Laury Guarnaccia, Léane Tremblay, Sandrine Laflamme-Thibault, Sharlène Côté, Patrice Tremblay, Julie Bouchard, Rubens Alexandre da Silva

Bibliographic record

VenuePhysical & Occupational Therapy In Geriatrics · 2021
Typearticle
Languageen
FieldHealth Professions
TopicBalance, Gait, and Falls Prevention
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanMcGill UniversityUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsNeurocognitiveFunctional impairmentPhysical medicine and rehabilitationCognitionPsychologyRehabilitationMedicineFalls in older adultsTest (biology)GerontologyClinical psychologyPhysical therapyPsychiatryHuman factors and ergonomicsPoison controlMedical emergency

Abstract

fetched live from OpenAlex

Aims: The assessment of the risk of falling in geriatric rehabilitation is often using standardized functional tests, which may be more complex but less representative in older adults with a neurocognitive disorder. The conceptual aim of this manuscript was thus to discuss the impact of adapted instructions on physical performance during standardized functional tests for older with neurocognitive disorders (NCD). Methods: Six topics were addressed: 1) current and global profile of falls in older, 2) fall assessment, 3) neurocognitive disorders in the older adults, 4) relationship between cognitive impairment and functional performance, 5) impact of the instructions on functional assessments in an older population, and finally 6) an overview of the future perspectives on possible adaptations for functional assessments in older adults with NCD. Conclusions: We believe that it is realistic and feasible to address adapted instructions to patients with NCD in clinical settings to optimize their assessment of their risk of falling.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.351
Teacher spread0.321 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venuePhysical & Occupational Therapy In GeriatricsSame topicBalance, Gait, and Falls PreventionFrench-language works237,207